// module.02 · capabilities

Systems design as a
first-class discipline.

Six capability nodes. Each backed by a stack we've run in production, methodologies we've written down, and measurable outcomes we've delivered.

node.SYS.01● active

Integrated Systems Design

Bind legacy monoliths to modern platforms with zero-downtime migration paths and reconciliation harnesses.

stack
TypeScriptRustPostgresKafkagRPC
methodologies
  • → Strangler-fig migration
  • → CDC + event sourcing
  • → Contract testing
cutover downtime
0s
data drift
< 0.001%
node.DATA.02● active

Data Processing Pipelines

Streaming and batch pipelines engineered for correctness under load and cost pressure.

stack
RustApache FlinkClickHouseIcebergdbt
methodologies
  • → Exactly-once semantics
  • → Backpressure design
  • → Cost-shaped SLOs
throughput
40k/s
p99 latency
< 180ms
node.PROG.03● active

Custom Computer Programming

Domain-specific systems where off-the-shelf software is a liability. Written by engineers who ship.

stack
GoRustTypeScriptPythonC++
methodologies
  • → Domain-driven design
  • → Property-based testing
  • → Formal invariants
code coverage
94%
escaped defects
0.3 / kLOC
node.PLAT.04● active

Platform Engineering

Internal developer platforms with observability, deploy tooling, and golden-path service templates.

stack
KubernetesTerraformOpenTelemetryArgoVault
methodologies
  • → Golden-path templates
  • → Progressive delivery
  • → SLO-driven release gates
deploy time
< 6min
MTTR
< 9min
node.SEC.05● active

Security & Compliance Architecture

SOC2, HIPAA, PCI-DSS-aligned designs with real controls, not policy theatre.

stack
OPAVaultCiliumSPIREFalco
methodologies
  • → Threat modeling
  • → IAM scoping
  • → Zero-trust segmentation
audit pass rate
100%
PCI scope reduction
-60%
node.AI.06● active

Applied ML Systems

Production ML with drift monitoring, feature stores, and honest evaluation. No demo-ware.

stack
PythonRayPyTorchFeastvLLM
methodologies
  • → Shadow deployment
  • → Human-in-the-loop QA
  • → Bias audits
false-positive rate
< 1%
inference p95
< 220ms